TEE-Assisted Time-Scale Database Management System on IoT devices
Jinjin Wang, Yizhou Du, Xiangyu Wang, Chengyan Ma, Di Lu, Ning Xi · 2023
Internet of Things (IoT) devices are usually vulnerable to attackers due to design imperfections and a lack of security measures. Since these devices are commonly used to collect data, safeguarding the security of data originating from them becomes an imperative priority. Encrypted database is a solution that takes both data security and availability into account. However, due to the resource-constrained nature of IoT devices, the implementation of existing encrypted databases poses challenges. Furthermore, existing encrypted databases only ensure data storage security, but they overlook data confidentiality while it is being processed in the device’s memory. To address the above issues, we devised a TEE-assisted encrypted database for managing sensitive information on embedded devices. By leveraging the protective capabilities offered by Trusted Execution Environment (TEE), our design can protect the confidentiality and integrity of data in a full life-cycle. Additionally, as IoT devices are frequently employed for collecting time-series data, we addressed the challenge of high-frequency data insertion by utilizing the Switchless-Feature and changing the data storage structure. Experiments demonstrate that our system’s data operation time is 30-60% faster than that of a similar solution, SMAUG [4], and it significantly enhances performance for high-frequency data insertion.